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plot_wordcloud


method plot_wordcloud(index=None, title=None, legend=False, figsize=(900, 600), filename=None, display=True, **kwargs)[source]
Plot a wordcloud from the corpus.

The text for the plot is extracted from the column named corpus. If there is no column with that name, an exception is raised.

Parametersindex: int, str, sequence or None, default=None
Index names or positions of the documents in the corpus to include in the wordcloud. If None, it selects all documents in the dataset.

title: str, dict or None, default=None
Title for the plot.

legend: bool or dict, default=False
Does nothing. Implemented for continuity of the API.

figsize: tuple, default=(900, 600)
Figure's size in pixels, format as (x, y).

filename: str or None, default=None
Name of the file. Use "auto" for automatic naming. If None, the figure is not saved.

display: bool or None, default=True
Whether to render the plot. If None, it returns the matplotlib figure.

**kwargs
Additional keyword arguments for the [Wordlcoud][wordlcoud] object.

Returnsgo.Figure or None
Plot object. Only returned if display=None.


See Also

plot_ngrams

Plot n-gram frequencies.


Example

>>> from atom import ATOMClassifier
>>> from sklearn.datasets import fetch_20newsgroups

>>> X, y = fetch_20newsgroups(
...     return_X_y=True,
...     categories=[
...         'alt.atheism',
...         'sci.med',
...         'comp.windows.x',
...     ],
...     shuffle=True,
...     random_state=1,
... )
>>> X = np.array(X).reshape(-1, 1)

>>> atom = ATOMClassifier(X, y)
>>> atom.textclean()
>>> atom.textnormalize()
>>> atom.plot_wordcloud()